【摘要】：當今組培苗接種工作仍以人工操作為主,部分企業(yè)嘗試研究接種機器人代替人工操作,但工作效率依然低下,原因是組培苗個體存在著巨大的差異性。在上述背景下,本課題開始設(shè)計分布式管理信息系統(tǒng),旨在提高接種工作效率和提高農(nóng)機與農(nóng)藝的融合度。本課題通過分布式系統(tǒng)架構(gòu)建立管理信息系統(tǒng),實現(xiàn)系統(tǒng)的異地化管理,確保數(shù)據(jù)在系統(tǒng)與數(shù)據(jù)庫之間正常傳輸。管理信息系統(tǒng)以多層前饋神經(jīng)網(wǎng)絡(luò)方法,即BP(back propagation)神經(jīng)網(wǎng)絡(luò)方法,初步建立組培苗機械作業(yè)適應(yīng)性的評價體系。利用評價體系對組培苗進行評價,根據(jù)評價結(jié)果,得到機械作業(yè)適應(yīng)性優(yōu)秀的組培苗的培養(yǎng)條件,為建立組培苗成長數(shù)學模型提供理論依據(jù)。通過數(shù)學模型培育出,個體差異性小且機械作業(yè)適應(yīng)性優(yōu)秀的組培苗,提高農(nóng)機與農(nóng)藝的融合度,從而提高組培苗接種工作的效率。主要工作如下:1.搭建管理信息系統(tǒng)平臺。分析馬鈴薯組培苗接種機器人工作情況,結(jié)合互聯(lián)網(wǎng)(web:world wide web)技術(shù),應(yīng)用WAMP(Windows+Apache+My SQL+PHP)工具,以分布式系統(tǒng)架構(gòu)搭建管理信息系統(tǒng)運行平臺。2.管理信息系統(tǒng)的設(shè)計與實現(xiàn)。設(shè)計數(shù)據(jù)庫,以便管理工作中產(chǎn)生的數(shù)據(jù);將管理信息系統(tǒng)劃分為16個模塊,如組培苗入庫、組培苗記錄、組培苗出庫等;可以實現(xiàn)系統(tǒng)與數(shù)據(jù)庫之間數(shù)據(jù)傳輸。3.本文以馬鈴薯組培苗為試驗對象,測量其相關(guān)參數(shù)(植株高度、莖稈直徑、節(jié)間長度、滿足節(jié)間長度要求的個數(shù)),結(jié)合實驗室已完成的相關(guān)試驗,建立組培苗機械作業(yè)適應(yīng)性的評價準則。4.建立系統(tǒng)評價體系。對標準BP神經(jīng)網(wǎng)絡(luò)進行改進(限幅轉(zhuǎn)移函數(shù)、累積誤差法),以組培苗植株高度、組培苗莖稈直徑、滿足節(jié)間長度要求的個數(shù)為評價條件,適合機械作業(yè)程度為評價指標,訓練BP神經(jīng)網(wǎng)絡(luò)得到評價體系。選取200株組培苗數(shù)據(jù)作為測試樣本,對評價體系進行測試,將結(jié)果與建立的評價準則進行對比,檢測評價體系的正確率,最后得到評價體系正確率為99%。將評價體系嵌入到系統(tǒng)中,完成管理信息系統(tǒng)建設(shè)。
[Abstract]:Nowadays, the work of tissue culture seedling vaccination is still dominated by manual operation. Some enterprises try to study the inoculating robot instead of artificial operation, but the work efficiency is still low, because there are great differences among tissue culture seedling individuals. Under the above background, this paper began to design a distributed management information system, in order to improve the efficiency of vaccination and improve the integration of agricultural machinery and agronomy. In this paper, the management information system is established through the distributed system architecture, which realizes the heterogeneous management of the system and ensures the normal transmission of data between the system and the database. In the management information system, the evaluation system of mechanical adaptability of tissue culture seedlings is established by using multi-layer feedforward neural network method, that is, BP (back propagation) neural network method. The evaluation system was used to evaluate the tissue culture plantlets. According to the evaluation results, the culture conditions of the tissue culture seedlings with excellent adaptability to mechanical operation were obtained, which provided a theoretical basis for the establishment of the mathematical model of the growth of tissue culture seedlings. Through the mathematical model, the tissue culture seedlings with small individual difference and excellent adaptability to mechanical operation were cultivated to improve the fusion degree of agricultural machinery and agronomy, so as to improve the efficiency of tissue culture seedling vaccination. The main work is as follows: 1. Build a management information system platform. The working situation of potato tissue culture seedling inoculating robot was analyzed. Combined with Internet (web:world wide web) technology, the running platform of management information system was built with distributed system architecture by using WAMP (Windows Apache My SQL PHP) tool. 2. Design and implementation of management information system. The database is designed to manage the data generated in the work; the management information system is divided into 16 modules, such as tissue culture seedling storage, tissue culture seedling record, tissue culture seedling out of the database and so on; the data transmission between the system and the database can be realized. In this paper, potato tissue culture seedlings were taken as the experimental object to measure the related parameters (plant height, stem diameter, Internode length, the number of Internode length to meet the requirements of Internode length), combined with the related experiments completed in the laboratory. The evaluation criteria of mechanical adaptability of tissue culture seedlings were established. 4. Establish a systematic evaluation system. The standard BP neural network was improved (limiting transfer function, cumulative error method). The plant height of tissue culture seedling, the diameter of stem of tissue culture seedling, the number of internode length satisfied were taken as the evaluation conditions, and the degree of mechanical operation was used as the evaluation index. The evaluation system is obtained by training BP neural network. The data of 200 tissue culture seedlings were selected as the test samples, and the evaluation system was tested. The results were compared with the established evaluation criteria, and the correct rate of the evaluation system was obtained. Finally, the correct rate of the evaluation system was 99%. The evaluation system is embedded into the system to complete the construction of management information system.
【學位授予單位】：東北農(nóng)業(yè)大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TP242;TP311.52

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